Lorenzo Pacchiardi

Orcid: 0000-0003-4760-7638

According to our database¹, Lorenzo Pacchiardi authored at least 10 papers between 2021 and 2024.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

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Bibliography

2024

Probabilistic Forecasting with Generative Networks via Scoring Rule Minimization.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2024

Leaving the barn door open for Clever Hans: Simple features predict LLM benchmark answers.

[BibT_eX]

[DOI]

Lorenzo Pacchiardi

Marko Tesic

Lucy G. Cheke

José Hernández-Orallo

CoRR, 2024

100 instances is all you need: predicting the success of a new LLM on unseen data by testing on a few instances.

[BibT_eX]

[DOI]

Lorenzo Pacchiardi

Lucy G. Cheke

José Hernández-Orallo

CoRR, 2024

How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2022

Statistical inference in generative models using scoring rules.

[BibT_eX]

[DOI]

Lorenzo Pacchiardi

PhD thesis, 2022

Score Matched Neural Exponential Families for Likelihood-Free Inference.

[BibT_eX]

[DOI]

Lorenzo Pacchiardi

Ritabrata Dutta

J. Mach. Learn. Res., 2022

Likelihood-Free Inference with Generative Neural Networks via Scoring Rule Minimization.

[BibT_eX]

[DOI]

Lorenzo Pacchiardi

Ritabrata Dutta

CoRR, 2022

2021

Using mobility data in the design of optimal lockdown strategies for the COVID-19 pandemic.

[BibT_eX]

[DOI]

PLoS Comput. Biol., 2021

ABCpy: A High-Performance Computing Perspective to Approximate Bayesian Computation.

[BibT_eX]

[DOI]

J. Stat. Softw., 2021

Probabilistic Forecasting with Conditional Generative Networks via Scoring Rule Minimization.

[BibT_eX]

[DOI]

CoRR, 2021

Lorenzo Pacchiardi

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